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The community detection in complex networks has become a major field of research. Disjoint community detection deals often with getting a partition of nodes where every node belongs to only one community. However, in social networks, individuals may belong to more than one community such as in co-purchasing field, a co-authorship of scientist papers or anthropological networks. We propose in this paper a method to find overlapping communities from pre-computed disjoint communities obtained by using the core detection label propagation. The algorithm selects candidates nodes for overlapping and uses belonging functions to decide the assignment or not of a candidate node to each of its neighbours communities. we propose and experiment in this paper several belonging functions, all based on the topology of the communities. These belonging functions are either based on global measures which are the density and the clustering coefficient or on average node measures which are the betweenness and the closeness centralities. We expose then a new similarity measure between two covers regarding the overlapping nodes. The goal is to assess the similarity between two covers that overlap several communities. We finally propose a comparative analysis with the literature algorithms. [ABSTRACT FROM AUTHOR]

All systems are likely to be affected by obsolescence. A component is considered obsolete when it is no longer manufactured or requested. Obsolescence must be taken into account, analysed and resolved effectively as it can lead to temporary or permanent stoppage of a system or make it impossible to repair it. The consequences of an obsolete entity must be minimised as they may have impacts, among others, on system characteristics such as availability or maintainability. These consequences can cascade through the system architecture. Understanding the propagation mechanisms can greatly contribute to obsolescence resilient design, but also to obsolescence management enabling a more effective determination of the scope of impact of actual or predicted obsolescence. The objective of this research work is to propose models to describe such propagation and to understand its principles. In fact, even if the obsolescence or rarefaction propagation is real and commonly accepted, there are no models describing its mechanisms. This paper focuses on two main points. First, it contributes to the concepts of obsolescence and rarefaction. Second, we propose descriptive and mathematical models of obsolescence and rarefaction propagation which allow to describe the likelihood of this propagation through the architecture of the system via two types of identified links, namely dependency and jump-up/jump-downs. These proposals are then illustrated through an example of a monitoring unit for a perfume bottle packaging line. After a discussion of the results obtained, the paper ends with the definition of future research pathways to ease the use of probabilistic inference tools for the exploitation of the proposed models. [ABSTRACT FROM AUTHOR]

Technologies, evolving at an ever faster pace, particularly in the electronics and IT sectors, lead inevitably systems to face the problems generated by obsolescence. Clearly, the manufacturer must be able to design systems so that an obsolescence problem has the least possible damaging or undesired consequences. The fact that a system remains as long as possible unaffected by changes imposed by obsolescence is called resilience. It, therefore, determines the ability of the system to continue providing its services while having at least one obsolete component, function or technology. The objective of this research work is to propose a modeling methodology and tools to ensure resilience to obsolescence; this resilience being directly defined by design choices. The methodology is based on the exploitation of modeled dependencies in the architecture of a system. The mapping of dependencies is done using different models obtained by applying a system engineering methodology, ARCADIA. The dependency model is then transformed into Bayesian networks to predict quantitatively not only the consequences of possible obsolescence issues in a given architecture but also to qualify the alternatives. This methodology, called Obsolescence Resilience By Construct, ORByC, is applied to the study of the rail signaling system. [ABSTRACT FROM AUTHOR]

Facility layout aims to arrange a set of facilities in a site. The main objective function is to minimize the total material handling cost under production-derived constraints. This problem has received much attention during the past decades. However, these works have mainly focused on solving a 2D layout problem, dealing with the footprints of pieces of equipment. The obtained results have been then adapted to the real spatial constraints of a workshop. This research work looks to take account of spatial constraints within a 3D space from the very first steps of problem solving. The authors use a approach by combining a genetic algorithm with A*, 〈GA,A*〉 research. The genetic algorithm generates possible arrangements and A* finds the shortest paths that products must travel in a restricted 3D space. The application allows to converge to a layout minimizing the total material handling cost. This approach is illustrated by its application on an example inspired by a valve assembly workshop in Tunisia and the results are discussed from two points of view. The first one consists in comparing the effect of the choice of the distance measurement technique on the handling cost. For this purpose, the results of the application of 〈GA,A*〉 are compared with those obtained by combining the genetic algorithm and two of the most commonly used distance measurements in the literature of the discipline, namely the Euclidean distance, 〈GA,Euclidean〉, and the rectilinear distance, 〈GA,rectilinear〉. Our results show that the proposed approach offers better results than those of 〈GA,rectilinear〉 whereas they are not as good as those obtained by the 〈GA,Euclidean〉 approach. The effectiveness of the 〈GA,A*〉 approach is then studied from the perspective of the effect of the algorithm used for the generation of candidate arrangements. The final results obtained from the application of 〈GA,A*〉 are then compared with those of the approach combining particle swarm optimization and A*, 〈PSO,A*〉. This comparison shows that the 〈GA,A*〉 approach obtains better results. Nevertheless, its convergence speed is lower than that of 〈PSO,A*〉. The paper ends with some conclusions and perspectives. [ABSTRACT FROM AUTHOR]

The objective of this document is to contribute to the modelling of engineering changes and their propagation. Usable in preliminary redesign activities, a new approach is suggested that allows greater efficiency. Given a product model, the idea is to use the experiments to calculate in advance the consequences of potential changes in continuous variables. These consequences are collected, analysed and structured in a dependency model, noted ⟨ Γ , Φ ⟩ , composed of a dependency graph Γ and its associated set of influence functions Φ . Bilateral influence functions, associated with arcs, quantify the dependencies between node pairs. Multilateral influence functions, identified by the application of the total differential theorem, define the dependencies between a node and all influential nodes on which it depends. Finally, the relative error is calculated by following the infinitesimal assumption of the total differential for each variables. Our findings show that such a dependency model is informative and allows effective prediction and evaluation of changes. The approach is illustrated by a geometric bicycle model. The results are discussed and future areas of research are finally presented. [ABSTRACT FROM AUTHOR]

This work proposes a new methodology and mathematical formulation to address the facility layout problem. The goal is to minimise the total material handling cost subjected to production-derived constraints. This cost is a function of the distance that the products should cover within the facility. The first idea is to use the A ∗ algorithm to identify the distances between workstations in a more realistic way. A ∗ determines the shortest path within the facility that contains obstacles and transportation routes. The second idea is to combine a genetic algorithm and the A ∗ algorithm with a homogenous methodology to improve the quality of the facility layouts. In an iterative way, the layout solution space is explored using the genetic algorithm. We study the impacts of the appropriate crossover and mutation operators and the values of the parameters used in this algorithm on the cost of the proposed arrangements. These operators and parameter values are fine-tuned using Monte Carlo simulations. The facility arrangements are all compared and discussed based on their material handling cost associated with the Euclidean distance, rectilinear distance, and A ∗ algorithm. Finally, we present a set of conclusions regarding the suggested methodology and discuss our future research goals. [ABSTRACT FROM AUTHOR]

One-off or Batch upgrading is the term given to the process of improving one or several operational instances of complex products or systems (e.g., trains, aircrafts, etc.) during their life span. Other products such as cars or personal computers are regularly improved through redesign, generation after generation; however, redesign never concerns only one or several instance(s). The main challenge presented in this paper is to provide a suitable framework to analyse one-off and batch upgrading processes. This framework targets at containing required concepts and drivers for upgrade problem posing. The axiom beneath this research is that the goal of upgradings is to improve the performances of products or systems. Upgrade-to-performance, UtP in short, represents this paradigm that will be defined and illustrated through examples. To reach this goal, necessary concepts are defined and linked together through a generic data model. The UtP data model can be used in a conceptual way clarifying the scope of the upgrading process. It can also be specialized to specific industrial domain and used as the main driver of the design of a database for a given upgrading projects. The use case reported concerns the conversion of a passenger train into an express freight where the focus is put on enlarging a coach’ door. The results are then discussed to figure out the links between the UtP problem-posing and problem-solving methods and the gaps to fill. Finally, further research niches are described. [ABSTRACT FROM AUTHOR]